This is a dashboard created using R Markdown and flexdashboard library. For more information see the official website.
Some random stuff.
[1] "Hello number 1" "Hello number 2" "Hello number 3"
[4] "Hello number 4" "Hello number 5" "Hello number 6"
[7] "Hello number 7" "Hello number 8" "Hello number 9"
[10] "Hello number 10" "Hello number 11" "Hello number 12"
[13] "Hello number 13" "Hello number 14" "Hello number 15"
[16] "Hello number 16" "Hello number 17" "Hello number 18"
[19] "Hello number 19" "Hello number 20" "Hello number 21"
[22] "Hello number 22"This is an equation in LaTeX:
\[ e^{i \pi} + 1 = 0 \]
This is a dashboard analyzing generated data with angles.
This is a note.
Hatla matla.
---
title: "Dashboard"
output:
flexdashboard::flex_dashboard:
# vertical_layout: scroll
vertical_layout: fill
# orientation: rows
source_code: embed
---
```{r setup, include=FALSE}
library(flexdashboard)
library(DT)
library(reshape2)
library(ggplot2)
library(plotly)
source('../plots_library.R')
```
Introduction {data-orientation=columns}
=============================================================================
Column {data-width=600}
-----------------------------------------------------------------------------
### Flex dashboards for R
This is a dashboard created using R Markdown and `flexdashboard` library.
For more information see the [official website](http://rmarkdown.rstudio.com/flexdashboard/index.html).
Column {data-width=400}
-----------------------------------------------------------------------------
### Data
Some random stuff.
```{r}
print(paste('Hello number', 1:22))
```
### Equations
This is an equation in LaTeX:
$$ e^{i \pi} + 1 = 0 $$
Dashboard {data-orientation=rows}
=============================================================================
This is a dashboard analyzing generated data with angles.
Row {.tabset}
-----------------------------------------------------------------------------
### Data
```{r}
# load data
angles <- read.table(file = '../data/angles.csv', sep = ';', dec = '.', header = T, stringsAsFactors = F)
class_names <- unique(angles$class)
angle_names <- unique(angles$angle_name)
# print data
datatable(angles, filter = 'top', options = list(paging = FALSE)) %>%
formatRound(columns = 'angle', digits = 2)
```
### Transformed data
```{r}
# transform data frame so we have separate column for each angle
angles_transformed <- dcast(data = angles, formula = class + step_index ~ angle_names, value.var = 'angle')
datatable(angles_transformed, filter = 'top', options = list(paging = FALSE)) %>%
formatRound(columns = angle_names, digits = 2)
```
Row {.tabset .tabset-fade}
-----------------------------------------------------------------------------
### Densities
```{r}
# plot data
ggplotly(ggplot(angles[angles$class == 'C1',], mapping = aes(x = angle, colour = angle_name)) + geom_density(adjust=2) + ggtitle('Class C1'))
```
> This is a note.
### Boxplots
```{r}
ggplotly(ggplot(angles, mapping = aes(y = angle, x = class, col = angle_name)) + geom_boxplot())
```
Storyboard {.storyboard}
=============================================================================
### Transformed data
```{r}
datatable(angles_transformed, filter = 'top', options = list(paging = FALSE)) %>%
formatRound(columns = angle_names, digits = 2)
```
### Boxplots
```{r}
ggplotly(ggplot(angles, mapping = aes(y = angle, x = angle_name, col = class)) + geom_boxplot())
```
### Histograms
```{r}
view_plots(path_to_plots = '../plots', plot_name_filter = 'Histogram interactive', type = 'iframe')
```
***
Hatla matla.